|
|
Interactive Analysis of the Efficiency of Technological Innovation and Reginal Economic Resilience:the Empirical Evidence of the Pearl River Delta |
Wang Peng1,Zhong Yuhua1,Yan Yue2 |
(1. School of Economics, Jinan University, Guangzhou 510632, China;2. College of Economics and Management, South China Agricultura University,Guangzhou 510642,China) |
|
|
Abstract China's economic development is in a critical period of transformation, and the previous development power is not enough to continue high-speed economic growth. We should emphasize the transformation of the economy to high-quality development. As one of the important strategies for high-quality economic development, can innovation-driven strategy effectively have a positive effect on economic development? It is also worthy of further discussion of how to reasonably measure the efficiency of scientific and technological innovation activities. While the foundation of China's internal economic development is constantly changing, COVID-19', anti globalization trend and a series of foreign negative factors are also constantly challenging China's economic resilience. As one of the regions with the most developed level of scientific and technological innovation and economic development in China, the Pearl River Delta is a representative region to study the relationship between scientific and technological innovation efficiency and economic resilience. This paper puts forward two research questions. The first is whether the current efficiency of scientific and technological R & D activities in the Pearl River Delta is efficient,and What the characteristics of temporal and spatial distribution are; the second is whether there is an interaction between scientific and technological innovation efficiency and economic resilience, and whether there will be phased differences in the direction and mechanism of influence between the two.#br# Nine cities in the Pearl River Delta are taken as the research object, their economic resilience and the two-stage efficiency of scientific and technological innovation activities are calculated and analyzed to obtain the relevant data sets of 9 cities in 13 years. The correlation between them is constructed by Tobit model and simultaneous equation model. In order to further broaden the connection ways between them, the study takes the perspective of industrial diversity to analyze the transmission role of industrial structure between economic resilience and the efficiency of scientific and technological innovation activities.#br#The results show that there are obvious differences in the efficiency of scientific and technological R & D stage and economic output stage in the Pearl River Delta, and there are also significant spatial heterogeneity in each stage. In the empirical process, there is a two-way causal relationship between the efficiency of the two stages of scientific and technological innovation and economic resilience in Tobit model, which will produce endogenous problems. The empirical results of simultaneous equations model prove that if considering the heterogeneity of region and time, the two-stage efficiency of scientific and technological innovation has a significant positive effect on economic resilience. Economic resilience can also support the two-stage efficiency, and the two-stage efficiency of scientific and technological innovation in areas with high economic resilience will be higher. When scientific and technological innovation activities are at different R & D levels, their innovation path and innovation content will not remain unchanged. Scientific and technological innovation activity is an uninterrupted activity. The development of R & D stage needs technical foreshadowing and support. Industrial diversification does not have a direct and significant impact on economic resilience, but it can indirectly affect economic resilience through the R & D stage of scientific and technological innovation.#br#This paper combines the research results of economic resilience theory, system efficiency theory and industrial diversification theory, takes the regional economic resilience and the efficiency of scientific and technological innovation activities as the research object. Different from the previous research, this paper creatively connects the economic resilience and the efficiency of scientific and technological innovation activities with simultaneous equations, Theoretical analysis and empirical research are carried out from an interactive research perspective, which expands the research ideas of the relationship between the two. The empirical results also support this theoretical hypothesis, and have guiding significance for building regional economic resilience and improving the efficiency of scientific and technological innovation activities. #br#First, compared with the economic output stage, the scientific and technological innovation stage should become the focus of government departments and enterprises;moreover, the differences in the efficiency of regional scientific and technological innovation are mainly concentrated in the stage of scientific and technological innovation, which urgently needs the government's macro-control to adapt the elements of scientific and technological innovation. Second, in areas with a higher level of high-tech innovation, relevant departments should pay attention to the non relevant diversification of structure and guide the integrated innovation across departments and fields when guiding the transformation and upgrading of industrial structure. Third, the diversification of regional industrial layout and the development of non related industries should be considered in policy formulation.#br#
|
Received: 20 July 2021
|
|
|
|
|
[1] 蔡昉. 人口转变、人口红利与刘易斯转折点 [J]. 经济研究, 2010, 45(4): 4-13.[2] 卫兴华, 侯为民. 中国经济增长方式的选择与转换途径 [J]. 经济研究, 2007, 4(7): 15-22.[3] SCHUMPETER J A.Business cycles[M].New York:McGrawHill,19-39.[4] MUELLER D C. Patents, research and development, and the measurement of inventive activity [J]. The Journal of Industrial Economics, 1966, 15(1): 26-37.[5] GRILICHES Z. R & D and the productivity slowdown [J]. The American Economic Review, 1980, 70(2): 343-348.[6] MANSFIELD E. Industrial R&D in Japan and the United States: a comparative study [J]. The American Economic Review, 1988, 78(2): 223-228.[7] 吴延兵. R&D与生产率——基于中国制造业的实证研究[J]. 经济研究, 2006, 4(11): 60-71.[8] 卢方元, 靳丹丹. 我国R&D投入对经济增长的影响——基于面板数据的实证分析 [J]. 中国工业经济, 2011, 4(3): 149-157.[9] JONES C I, WILLIAMS J C. Too much of a good thing? the economics of investment in R&D[J]. Journal of Economic Growth, 2000, 5(1): 65-85.[10] ZHONG W, YUAN W, LI S X, et al. The performance evaluation of regional R&D investments in China: an application of DEA based on the first official China economic census data [J]. Omega, 2011, 39(4): 447-455.[11] 严成樑, 龚六堂. R&D规模、R&D结构与经济增长[J]. 南开经济研究, 2013, 4(2): 3-19.[12] PIKE A, DAWLEY S, TOMANEY J. Resilience, adaptation and adaptability[J]. Cambridge journal of regions, economy and society, 2010, 3(1): 59-70.[13] DAWLEY S, PIKE A, TOMANEY J. Towards the resilient region[J]. Local Economy, 2010, 25(8): 650-667.[14] MARTIN R. Regional economic resilience, hysteresis and recessionary shocks[J]. Journal of Economic Geography, 2012, 12(1): 1-32.[15] HILL E, CLAIR T S, WIAL H, et al. Urban and regional policy and its effects: building resilient regions[M]. Brookings Institution Press,2012: 193-274.[16] SIMMIE J, MARTIN R. The economic resilience of regions: towards an evolutionary approach[J]. Cambridge Journal of Regions, Economy and Society, 2010, 3(1): 27-43.[17] GLAESER E L. Triumph of the city: how our greatest invention makes us richer, smarter, greener, healthier, and happier (an excerpt) [J]. Journal of Economic Sociology, 2013, 14(4): 75-94.[18] FILIPPETTI A, GKOTSIS P, VEZZANI A, et al. Are innovative regions more resilient? evidence from Europe in 2008–2016 [J]. Economia Politica, 2020, 37(3): 807-832.[19] CALIGNANO G, DE SIENA L. Does innovation drive economic resistance? not in Italy, at least[J]. Rivista geografica Italiana, 2020(3): 31-49.[20] 孟卫东, 王清. 区域创新体系科技资源配置效率影响因素实证分析[J]. 统计与决策, 2013, 4(4): 96-99.[21] 兰海, 吴悦, 王丹. 基于DEA和Malmquist指数的青海省科技创新效率研究[J]. 科技管理研究, 2021, 41(17): 40-46.[22] 刘钒, 邓明亮. 基于改进超效率DEA模型的长江经济带科技创新效率研究[J]. 科技进步与对策, 2017, 34(23): 48-53.[23] TONE K. A slacksbased measure of superefficiency in data envelopment analysis[J]. European Journal of Operational Research, 2002, 143(1): 32-41.[24] 樊华, 周德群. 中国省域科技创新效率演化及其影响因素研究[J]. 科研管理, 2012, 33(1):26,10-18.[25] 彭晓静. 京津冀城市群创新效率及影响因素研究[J]. 技术经济与管理研究, 2021, 4(2): 118-122.[26] 刘汉初, 樊杰, 周侃. 中国科技创新发展格局与类型划分——基于投入规模和创新效率的分析[J]. 地理研究, 2018, 37(5): 910-924.[27] 张振, 赵儒煜, 杨守云. 东北地区产业结构对区域经济韧性的空间溢出效应研究[J]. 科技进步与对策, 2020, 37(5): 37-46.[28] 方创琳, 王岩. 中国城市脆弱性的综合测度与空间分异特征[J]. 地理学报, 2015, 70(2): 234-247.[29] 刘逸, 纪捷韩, 张一帆, 等. 粤港澳大湾区经济韧性的特征与空间差异研究 [J]. 地理研究, 2020, 39(9): 2029-2043.[30] 谭俊涛, 赵宏波, 刘文新, 等. 中国区域经济韧性特征与影响因素分析[J]. 地理科学, 2020, 40(2): 173-181.[31] FINGLETON B, GARRETSEN H, MARTIN R. Recessionary shocks and regional employment: evidence on the resilience of UK regions[J]. Journal of regional science, 2012, 52(1): 109-133.[32] LAGRAVINESE R. Economic crisis and rising gaps North–South: evidence from the Italian regions [J]. Cambridge Journal of Regions, Economy and Society, 2015, 8(2): 331-342.[33] 李福柱. 演化经济地理学的理论框架与研究范式:一个文献综述 [J]. 经济地理, 2011, 31(12): 1975-1980,1994.[34] 孙晓华, 柴玲玲. 相关多样化, 无关多样化与地区经济发展——基于中国 282 个地级市面板数据的实证研究[J]. 中国工业经济, 2012, 4(6): 5-17. |
|
|
|